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Penerapan Model Spatial Autoregressive pada Data Penetapan Warisan Budaya Takbenda di Indonesia

Authors

  • Tsuroyya Salsabil Universitas Padjadjaran
  • Dianne Amor Kusuma Universitas Padjadjaran
  • Budi Nurani Ruchjana Universitas Padjadjaran

Keywords:

Warisan Budaya Takbenda (WBTb), Spatial Autoregressive (SAR), Matriks Pembobot, Intangible Cultural Heritage, Spatial Autoregressive (SAR), Weighting Matrix

Abstract

Warisan Budaya Takbenda (WBTb) dengan sifatnya yang dapat berlalu dan hilang dalam waktu seiring perkembangan zaman membutuhkan perlindungan lebih. Salah satu program pelindungan yang dilakukan oleh pemerintah adalah penetapan WBTb. Kegiatan penetapan ini memiliki keterbatasan dalam menggambarkan pengaruh lokasi dan prediksi data penetapan WBTb di Indonesia. Sedangkan, WBTb di suatu wilayah bisa saja saling memengaruhi dengan WBTb di wilayah lain di sekitarnya. Salah satu dari model yang dapat digunakan adalah Model Spatial Autoregressive (SAR). Oleh karena itu, penelitian ini bertujuan untuk menerapkan Model Spatial Autoregressive (SAR) orde satu untuk menggambarkan pengaruh lokasi dan prediksi data penetapan WBTb di Indonesia. Berdasarkan hasil pemilihan model terbaik dengan indikator nilai AIC dan pseudo-  model yang terpilih untuk prediksi data penetapan WBTb di Indonesia adalah Model SAR orde satu dengan matriks pembobot Queen Contiguity.

 

The Application of Spatial Autoregressive Model to the Data of
Intangible Cultural Heritage Designation in Indonesia

Cultural Heritage with intangible characteristics (WBTb), which can fade and disappear over time due to the development of the era, requires greater protection. One of the protective programs carried out by the government is the designation of WBTb. However, the designation process has limitations in depicting the influence of location and predicting the data of WBTb designation in Indonesia. Meanwhile, WBTb in one region may influence the WBTb in neighboring regions. One of the models that can be used is the Spatial Autoregressive Model (SAR). Therefore, this research aims to apply the first-order Spatial Autoregressive Model (SAR) to depict the influence of location and predict the data of WBTb designation in Indonesia. Based on the results of selecting the best model using the indicators of AIC value and pseudo- , the chosen model for predicting the data of WBTb designation in Indonesia is the first-order SAR model with Queen Contiguity weight matrix.

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Published

2023-11-30